Name
Abstract | ||
|---|---|---|
We present an automatic optimization approach to outfit synthesis. Given the hair color, eye color, and skin color of the input body, plus a wardrobe of clothing items, our outfit synthesis system suggests a set of outfits subject to a particular dress code. We introduce a probabilistic framework for modeling and applying dress codes that exploits a Bayesian network trained on example images of real-world outfits. Suitable outfits are then obtained by optimizing a cost function that guides the selection of clothing items to maximize the color compatibility and dress code suitability. We demonstrate our approach on the four most common dress codes: Casual, Sportswear, Business-Casual, and Business. A perceptual study validated on multiple resultant outfits demonstrates the efficacy of our framework. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2366145.2366153 | ACM Trans. Graph. |
Keywords | Field | DocType |
particular dress code,dress code suitability,dress code,automatic optimization,outfits subject,eye color,common dress code,color compatibility,outfit synthesis,clothing item,hair color,skin color,variety,optimization,perception,procedural modeling | Dress code,Computer vision,Procedural modeling,Computer science,Clothing,Bayesian network,Artificial intelligence,Casual,Perceptual study,Probabilistic framework | Journal |
Volume | Issue | ISSN |
31 | 6 | 0730-0301 |
Citations | PageRank | References |
19 | 0.72 | 30 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lap-Fai Yu | 1 | 316 | 24.87 |
| Sai Kit Yeung | 2 | 420 | 27.17 |
| Demetri Terzopoulos | 3 | 14080 | 4210.64 |
| Tony F. Chan | 4 | 8733 | 659.77 |